Analysis Of Spotify Top Songs During Covid-19 Pandemic
Keywords:Spotify, API, Spotify library, feature extraction, python
During the COVID-19 pandemic, many behaviors or habits have changed, especially in the internet audio-visual field which has increased significantly, one example is Spotify as an audio service provider. Not all songs on Spotify are popular or in the Top Songs. This study aims to examine whether there were differences in popular songs during the pandemic and before the pandemic and to determine the relationship between factors of popular songs on Spotify during the COVID-19 pandemic. The method used is to fetch Spotify songs via the API (Application Programming Interface) with the Spotify Python library. The features obtained are compared with the boxplot. The correlation between the Danceability and Energy features is obtained which ranges from 0.5-0.7, while the other features require further preprocessing because the values are not the same and are empty. This shows that every song that is considered good Danceability and Energy ranges from 0.5 to 0.7, regardless of singer, genre, or other song features.